关联规则挖掘在市场监管工作中的应用

摘要

关联规则是为了挖掘出隐藏在数据中的相互关系，找出所有能把一组事件或数据项与另一组事件或数据项联系起来的规则，从而辅助决策者进行决策。结合市场监督管理部门监管数据的实际情况，抽取市场主体部分基本信息和监管部门录入的违规、违法数据生成违规违法事务数据库，再将事务数据库转换为布尔矩阵，采用基于向量内积的关联规则挖掘方法生成频繁项集，进行关联规则挖掘。实验结果表明，该方法能够快速、准确地挖掘出相应的关联规则，符合市场监管部门日常工作的实际情况，对实际工作具有一定的指导意义。%Association rule mining is to dig out hidden relationships in data, it can find out all the relationship of a set of events or data items with another set of events or data items, which assist policymaker to make decisions.Combining with market super-vision and management department’ s situation, this paper generated transaction database from the basic market information, vio-lations and illegal entry data of market entities, converted this transaction database to a Boolean matrix, and then generated fre-quent item sets and association rules by the method based on vector inner product.The result shows that it can find out association rules from the transaction database correctly and meet to the actual situation of market supervision and management department.